DocumentCode :
1944182
Title :
Application of Multi Objective Evolutionary Programming to Combined Economic Emission Dispatch Problem
Author :
Jeyakumar, D.N. ; Venkatesh, P. ; Lee, Kwang Y.
Author_Institution :
P.S.N.A Coll. of Eng., Dindigul
fYear :
2007
fDate :
12-17 Aug. 2007
Firstpage :
1162
Lastpage :
1167
Abstract :
This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bi-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.
Keywords :
Pareto optimisation; emission; evolutionary computation; load dispatching; power system economics; distributed Pareto optimal solutions; economic emission dispatch problem; fuel cost; multiobjective evolutionary programming; selection mechanism; six-unit system; three-unit system; weighted sum method; Atmosphere; Cost function; Environmental economics; Fuel economy; Genetic algorithms; Genetic programming; Power generation; Power generation economics; Power system economics; Testing; Combined economic emission dispatch; Pareto optimal solutions; evolutionary programming; non-dominated solution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2007.4371122
Filename :
4371122
Link To Document :
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